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Human beings use models all the time. Our observations, reflections and interpretations are all about creating mental models. Words themselves are models – a representation of reality. Just as the word apple is not the apple itself, a word, any word, is a concept we understand through agreement. Models provide a basis for conversation.
Friends at the Sente Corporation have put it this way:
“Depending on how you look at it, anything can be a model. Even reality – from one vantage point – is merely our own electro-chemical processing of narrow bandwidths taken from a sea of information”.
Why do we create models? Good models simplify our complex world, enabling us to communicate and appropriate complex ideas, notions, theories, and so on effectively and efficiently. We make our models to a scale where what they represent becomes understandable on an intuitive level. They enable us to develop the comprehension and insight from which we can begin to experiment. And through this, we learn.
In the context of enterprise, models enable us to examine a situation, analyse it and then draw out plans. Many of the concepts we grapple with in today’s organisations are so complex they are beyond the limits of our intuitive comprehension. Through modelling we attempt to strip away these layers of complexity in order for us to understand the context of the enterprise, the components within it and their relationships to each other and the external eco-system.
They do have their limitations. Models are fundamentally ‘reductionist’ in nature and there’s a balance to be struck between making the model sufficiently abstract that it can be understood intuitively whilst avoiding over-simplification. For example, in breaking processes down to constituent parts, the nature of the whole – the systemic dimension of the organisation – is all too often left neglected. The decomposition omits many of the complex interactions around a process, which is just a logical, linear sequence of activities. To document all such interactions would involve a mammoth effort of analysis, so the trick is to find the right mixture of reductionism and ‘holism’ or ‘systems thinking’. Cybernetics helps our understanding too, and I’ll come back to these points in later posts.
There is one fundamental pitfall to avoid when working with models: we must never forget that all our models – be they process maps, mind maps, spread-sheets, stories, physical or conceptual models – are abstractions. Therefore it is vitally important we remain vigilant in revisiting and revising them regularly, cognisant of the fact that, as George Box put it: “All models are wrong. Some models are useful”.
We must learn to be constantly critical and questioning, otherwise the very models we have constructed can be our own downfall as we cling on to them, attached to the comfort of a reality we perceive that may not, in fact, be appropriate. The only way of achieving a shift in our own perspective is through conversation. An intervention in our self-perpetuating thought processes can – if we are open to it – change our view of the world. Or our business.
At Innovation Arts, when we work with clients facing complex issues, we apply a rigorous approach to modelling. Dialogue and iteration are key to our approach, both during the Architecting and Building phases of solution design, but also when the new model is put to Use.